ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis. Data Migration 2.

Hadoop 52

Hadoop Project Big Data Healthcare 52

The Pragmatic Engineer

JUNE 13, 2023

The company’s largest data cluster is 20-30PB (petabytes: 1PB is 1,000 terabytes or 1M gigabytes). Ten years ago, this data cluster was 300GB as a Hadoop cluster; that’s around a 100,000-fold increase in data stored! The company runs 4 data centers: in the US and Europe, with two in Asia.

Cloud 242

Cloud Database Utilities BI 242

ProjectPro

MARCH 17, 2014

Big data and hadoop are catch-phrases these days in the tech media for describing the storage and processing of huge amounts of data. Over the years, big data has been defined in various ways and there is lots of confusion surrounding the terms big data and hadoop. What is Big Data according to IBM?

Hadoop 52

Hadoop Big Data Unstructured Data Data Analytics 52

Monte Carlo

MAY 28, 2024

In batch processing, this occurs at scheduled intervals, whereas real-time processing involves continuous loading, maintaining up-to-date data availability. Data Validation : Perform quality checks to ensure the data meets quality and accuracy standards, guaranteeing its reliability for subsequent analysis.

Data Ingestion 52

Data Ingestion Architecture Designing Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

Most of the Data engineers working in the field enroll themselves in several other training programs to learn an outside skill, such as Hadoop or Big Data querying, alongside their Master's degree and PhDs. Kafka Kafka is an open-source processing software platform.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

ProjectPro

MARCH 23, 2015

was intensive and played a significant role in processing large data sets, however it was not an ideal choice for interactive analysis and was constrained for machine learning, graph and memory intensive data analysis algorithms. In one of our previous articles we had discussed about Hadoop 2.0

Hadoop 40

Hadoop Big Data Architecture Kafka 40

Christophe Blefari

JUNE 21, 2024

Both companies have added Data and AI to their slogan, Snowflake used to be The Data Cloud and now they're The AI Data Cloud. One way to read data platforms When we look at platforms history what characterises evolution is the separation (or not) between the engine and the storage. But what is doing Tabular?

Metadata 147

Metadata Data Warehouse BI MySQL 147

Data Engineering Podcast

DECEMBER 16, 2019

Many metadata management systems are simply a service layer on top of a separate data storage engine. Many metadata management systems are simply a service layer on top of a separate data storage engine. Can you explain how Marquez is architected and how the design has evolved since you first began working on it?

Metadata 100

Metadata PostgreSQL Datasets Data Warehouse 100

ProjectPro

JULY 21, 2021

As a big data architect or a big data developer, when working with Microservices-based systems, you might often end up in a dilemma whether to use Apache Kafka or RabbitMQ for messaging. Rabbit MQ vs. Kafka - Which one is a better message broker? Table of Contents Kafka vs. RabbitMQ - An Overview What is RabbitMQ?

Kafka 52

Kafka Big Data Java Architecture 52

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. Data storage and processing. Apache Hadoop.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

AUGUST 21, 2015

With the help of ProjectPro’s Hadoop Instructors, we have put together a detailed list of big data Hadoop interview questions based on the different components of the Hadoop Ecosystem such as MapReduce, Hive, HBase, Pig, YARN, Flume, Sqoop , HDFS, etc. What is the difference between Hadoop and Traditional RDBMS?

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

NOVEMBER 7, 2016

Understanding the Hadoop architecture now gets easier! This blog will give you an indepth insight into the architecture of hadoop and its major components- HDFS, YARN, and MapReduce. We will also look at how each component in the Hadoop ecosystem plays a significant role in making Hadoop efficient for big data processing.

Hadoop 40

Hadoop Architecture IT Big Data 40

AltexSoft

OCTOBER 30, 2021

Data engineer’s integral task is building and maintaining data infrastructure — the system managing the flow of data from its source to destination. This typically includes setting up two processes: an ETL pipeline , which moves data, and a data storage (typically, a data warehouse ), where it’s kept.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

Edureka

FEBRUARY 9, 2023

Azure Data Engineering is a rapidly growing field that involves designing, building, and maintaining data processing systems using Microsoft Azure technologies. As a certified Azure Data Engineer, you have the skills and expertise to design, implement and manage complex data storage and processing solutions on the Azure cloud platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

NOVEMBER 28, 2023

Concepts of IaaS, PaaS, and SaaS are the trend, and big companies expect data engineers to have the relevant knowledge. Kafka Kafka is one of the most desired open-source messaging and streaming systems that allows you to publish, distribute, and consume data streams. ETL is central to getting your data where you need it.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

U-Next

AUGUST 17, 2022

Because of this, all businesses—from global leaders like Apple to sole proprietorships—need Data Engineers proficient in SQL. NoSQL – This alternative kind of data storage and processing is gaining popularity. They’ll come up during your quest for a Data Engineer job, so using them effectively will be quite helpful.

Data Engineering 52

Data Engineering Data Engineer Database-centric Pipeline-centric 52

Knowledge Hut

APRIL 25, 2023

Data modeling: Data engineers should be able to design and develop data models that help represent complex data structures effectively. Data processing: Data engineers should know data processing frameworks like Apache Spark, Hadoop, or Kafka, which help process and analyze data at scale.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

ProjectPro

SEPTEMBER 16, 2021

NoSQL databases are the new-age solutions to distributed unstructured data storage and processing. The speed, scalability, and fail-over safety offered by NoSQL databases are needed in the current times in the wake of Big Data Analytics and Data Science technologies.

NoSQL 52

NoSQL Database Hadoop Big Data 52

AltexSoft

JULY 18, 2023

This module can ingest live data streams from multiple sources, including Apache Kafka , Apache Flume , Amazon Kinesis , or Twitter, splitting them into discrete micro-batches. Netflix leverages Spark Streaming and Kafka for near real-time movie recommendations.

Big Data 52

Big Data Data Process Process Hadoop 52

Cloud Academy

JANUARY 27, 2022

Apache Kafka Amazon MSK and Kafka Under the Hood Apache Kafka is an open-source streaming platform. Learn about the AWS-managed Kafka offering in this course to see how it can be more quickly deployed. Apache Hadoop Introduction to Google Cloud Dataproc Hadoop allows for distributed processing of large datasets.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Big Data Tools

SEPTEMBER 6, 2021

It hasn’t had its first release yet, but the promise is that it will un-bias your data for you! rc0 – If you like to try new releases of popular products, the time has come to test Kafka 3 and report any issues you find on your staging environment! At least until Fairlens came on the scene. How cool is that? Support for Scala 2.12

Data Engineering 52

Data Engineering Data Engineer Engineering Big Data Tools 52

Knowledge Hut

DECEMBER 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases. Knowledge of Hadoop, Spark, and Kafka.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

AltexSoft

MARCH 14, 2023

Additionally, this modularity can help prevent vendor lock-in, giving organizations more flexibility and control over their data stack. Many components of a modern data stack (such as Apache Airflow, Kafka, Spark, and others) are open-source and free. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Silectis

JANUARY 3, 2021

Big Data Large volumes of structured or unstructured data. Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Edureka

FEBRUARY 9, 2023

In this blog on “Azure data engineer skills”, you will discover the secrets to success in Azure data engineering with expert tips, tricks, and best practices Furthermore, a solid understanding of big data technologies such as Hadoop, Spark, and SQL Server is required.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Knowledge Hut

NOVEMBER 19, 2023

As a result, data engineers working with big data today require a basic grasp of cloud computing platforms and tools. Businesses can employ internal, public, or hybrid clouds depending on their data storage needs, including AWS, Azure, GCP, and other well-known cloud computing platforms.

Data Engineering 52

Data Engineering Data Engineer Engineering PostgreSQL 52

Knowledge Hut

NOVEMBER 17, 2023

You must be able to create ETL pipelines using tools like Azure Data Factory and write custom code to extract and transform data if you want to succeed as an Azure Data Engineer. Big Data Technologies You must explore big data technologies such as Apache Spark, Hadoop, and related Azure services like Azure HDInsight.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

NOVEMBER 15, 2021

DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Apache Spark is also quite versatile, and it can run on a standalone cluster mode or Hadoop YARN , EC2, Mesos, Kubernetes, etc. Presto allows you to query data stored in Hive, Cassandra, relational databases, and even bespoke data storage.

Big Data 52

Big Data Project Metadata Programming Language 52

Monte Carlo

MAY 14, 2024

Let’s revisit how several of those key table formats have emerged and developed over time: Apache Avro : Developed as part of the Hadoop project and released in 2009, Apache Avro provides efficient data serialization with a schema-based structure.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Ascend.io

SEPTEMBER 14, 2023

Use Case: Transforming monthly sales data to weekly averages import dask.dataframe as dd data = dd.read_csv('large_dataset.csv') mean_values = data.groupby('category').mean().compute() compute() Data Storage Python extends its mastery to data storage, boasting smooth integrations with both SQL and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Python Engineering 52

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Notice how Snowflake dutifully avoids (what may be a false) dichotomy by simply calling themselves a “data cloud.” Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

JUNE 23, 2023

You should be well-versed in Python and R, which are beneficial in various data-related operations. Apache Hadoop-based analytics to compute distributed processing and storage against datasets. Machine learning will link your work with data scientists, assisting them with statistical analysis and modeling. What is HDFS?

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Project Coding 52

Big Data Tools

SEPTEMBER 6, 2021

It hasn’t had its first release yet, but the promise is that it will un-bias your data for you! rc0 – If you like to try new releases of popular products, the time has come to test Kafka 3 and report any issues you find on your staging environment! At least until Fairlens came on the scene. How cool is that? Support for Scala 2.12

Data Engineering 40

Data Engineering Data Engineer Engineering Big Data Tools 40

ProjectPro

MAY 30, 2016

The next in the series of articles highlighting the most commonly asked Hadoop Interview Questions, related to each of the tools in the Hadoop ecosystem is - Hadoop HDFS Interview Questions and Answers. HDFS vs GFS HDFS(Hadoop Distributed File System) GFS(Google File System) Default block size in HDFS is 128 MB.

Hadoop 40

Hadoop Metadata Big Data Portfolio 40

ProjectPro

AUGUST 11, 2021

Is Snowflake a data lake or data warehouse? Is Hadoop a data lake or data warehouse? ironSource has to collect and store vast amounts of data from millions of devices. ironSource started making use of Upsolver as its data lake for storing raw event data. Is Hadoop a data lake or data warehouse?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Monte Carlo

JUNE 2, 2024

These languages are used to write efficient, maintainable code and create scripts for automation and data processing. Databases and Data Warehousing: Engineers need in-depth knowledge of SQL (88%) and NoSQL databases (71%), as well as data warehousing solutions like Hadoop (61%).

Engineering 52

Engineering Amazon Web Services Data Science AWS 52